Transcript LEC5a_Network Visualizationx

Lecture 04:
Introduction to Network Visualization
October 21st, 2016
Presented by: Anum Masood (TA)
Network Analysis Workflow
• Load Networks e.g. proteins, enzymes, facebook, twitter
– Import network data
• Load Attributes e.g. data related to the objects
– Get data about networks
• Analyze and Visualize Networks
• Save the network
Network Visualization and Analysis
Outline
• Network introduction
• Network visualization
• Cytoscape software tool for network visualization and
analysis
• Network analysis
Networks
• Represent relationships
– Physical, relational, genetic, functional interactions
• Useful for discovering relationships in large data sets
– Better than tables in Excel
• Visualize multiple data types together
– See interesting patterns
• Network analysis
=> Biological Networks as Example
Biological Pathways/Networks?
Six Degrees of Separation
• Everyone in the world is connected
by at most six links
• Which path should we take?
• Shortest path by breadth first search (BFS)
– If two nodes are connected, will find the shortest path
between them
• Biologically related? How?
http://www.time.com/time/techtime/200406/community.html
Applications of Network Biology
•
Gene Function Prediction –
shows connections to sets of
genes/proteins involved in same
biological process
•
Detection of protein
complexes/other modular
structures –
discover modularity & higher order
organization (motifs, feedback
loops)
•
Network evolution –
biological process(es)
conservation across species
•
Prediction of new interactions
and functional associations –
Statistically significant domaindomain correlations in protein
interaction network to predict
protein-protein or genetic
interaction
jActiveModules, UCSD
PathBlast, UCSD
MCODE, University of Toronto
DomainGraph, Max Planck Institute
humangenetics-amc.nl
Applications of Network Informatics in Disease
•
Identification of disease
subnetworks – identification of
disease network subnetworks that
are transcriptionally active in
disease.
•
Subnetwork-based diagnosis –
source of biomarkers for disease
classification, identify interconnected
genes whose aggregate expression
levels are predictive of disease state
•
Subnetwork-based gene
association – map common
pathway mechanisms affected by
collection of genotypes
Agilent Literature Search
PinnacleZ, UCSD
Mondrian, MSKCC
humangenetics-amc.nl
June 2009
What’s Missing?
• Dynamics
– Pathways/networks represented as static processes
• Difficult to represent a feedback loop
– More detailed mathematical representations exist that
handle these e.g. Kinetic modeling
• Need to accumulate or estimate comprehensive kinetic
information
• Detail – atomic structures
• Context – cell type, developmental stage
What Have We Learned?
• Networks are useful for seeing relationships in large data
sets
• Important to understand what the nodes and edges
mean
• Important to define the biological question - know what
you want to do with your gene list or network
• Many methods available for gene list and network
analysis
– Good to determine your question and search for a solution
– Or get to know many methods and see how they can be applied
to your data
Network Visualization Outline
• Automatic network layout
• Visual features
• Visually interpreting a network
Network Representations
Automatic network layout
Automatic network layout
• Force-directed: nodes repel and edges pull
• Good for up to 500 nodes
– Bigger networks give hairballs - Reduce number of edges
• Try directed first, or hierarchical for tree-like networks
• Tips for better looking networks
– Manually adjust layout
– Load network into a drawing program (e.g. Illustrator) and
adjust labels
Visual Features
• Node and edge attributes
– Text (string), integer, float,
Boolean, list
– E.g. represent interaction
attributes
• Visual attributes
– Node, edge visual properties
– Colour, shape, size, borders,
opacity...
Visually Interpreting a Network
Data relationships
Guilt-by-association
Dense clusters
Global relationships
What Have We Learned?
• Automatic layout is required to visualize networks
• Networks help you visualize interesting relationships in
your data
• Avoid hairballs by focusing analysis
• Visual attributes enable multiple types of data to be
shown at once – useful to see their relationships
Network Visualization and Analysis using
Cytoscape
• Network visualization and analysis using Cytoscape
software
• Cytoscape basics
• Cytoscape network analysis examples
http://cytoscape.org
Network
visualization
and analysis
Pathway comparison
Literature mining
Gene Ontology analysis
Active modules
Complex detection
Network motif search
Network Analysis using Cytoscape
Find a problem with huge
dataset whose network is
required.
Databases
Literature
Network
Analysis
Network
Information
Expert knowledge
Experimental Data
Manipulate Networks
Automatic Layout
Filter/Query
Interaction Database Search
Active Community
http://www.cytoscape.org
• Help
– Tutorials, case studies
– Mailing lists for discussion
– Documentation, data sets
• >160 Plugins/Apps Extend Functionality
– The app store: http://apps.cytoscape.org/
– Build your own, requires programming
What Have We Learned?
• Cytoscape is a useful, free software tool for network
visualization and analysis
• Provides basic network manipulation features
• Plugins/Apps are available to extend the functionality
Links
• http://ebeshero.github.io/thalaba/cytosc.html
• https://archaeologicalnetworks.files.wordpress.com/201
3/11/brughmans-2013-network-analysis-with-cytoscapetutorial.pdf
• http://web.mit.edu/cytoscape_v3.3.0/Cytoscape3_3_0M
anual.pdf
• http://opentutorials.cgl.ucsf.edu/index.php/Tutorial:Intro
duction_to_Cytoscape
Cytoscape Demo
Version 2.8.2
www.cytoscape.org
FYI
Desktop
Network manager
CytoPanels
Canvas
Network overview
Attribute browser
yFiles Organic
yFiles Circular
Network Layout
• 15 algorithms available through plugins
• Demo: Move, zoom/pan, rotate, scale, align
Create Subnetwork
Create Subnetwork
Visual Style
• Customized views of experimental data in a network
context
• Network has node and edge attributes
• E.g. expression data, GO function, interaction type
• Mapped to visual attributes
• E.g. node/edge size, shape, colour…
• E.g. Visualize gene expression data as node colour
gradient on the network
Visual
Style
Load “Your Favorite Network”
Visual
Style
Load “Your Favorite Expression”
Dataset
Visual Style
Map expression values to node colours using a continuous mapper
Visual
Style
Expression data mapped
to node colours
Network Filtering
Interaction Database Search
Cytoscape Lab
• Cytoscape – expression data visualization
– Load the sample network file: galFiltered.sif
– Lay it out – try different layouts
– Load expression data - galExpData.pvals
• Use File->Import->Attribute from Table
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Examine node attributes
Visualize gene expression data using the Visual Mapper
Install the VistaClara plugin from the plugin manager
Play the expression data as a movie
Cytoscape 2.8 Tips & Tricks
• “Root graph”
– “There is one graph to rule them all….”
– The networks in Cytoscape are all “views” on a single graph.
– Changing the attribute for a node in one network will also
change that attribute for a node with the same ID in all other
loaded networks
– There is no way to “copy” a node and keep the same ID
– Make a copy of the session
Cytoscape 2.8 Tips & Tricks
• Network views
– When you open a large network, you will not get a view by
default
– To improve interactive performance, Cytoscape has the concept
of “Levels of Detail”
• Some visual attributes will only be apparent when you zoom in
• The level of detail for various attributes can be changed in the
preferences
• To see what things will look like at full detail:
– ViewShow Graphics Details
Cytoscape 2.8 Tips & Tricks
• Sessions
– Sessions save pretty much everything:
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•
•
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Networks
Properties
Visual styles
Screen sizes
– Saving a session on a large screen may require some resizing
when opened on your laptop
Cytoscape 2.8 Tips & Tricks
• Logging
– By default, Cytoscape writes it’s logs to the Error Dialog:
HelpError Dialog
– Can change a preference to write it to the console
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•
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EditPreferencesProperties…
Set logger.console to true
Don’t forget to save your preferences
Restart Cytoscape
– (can also turn on debugging: cytoscape.debug, but I don’t
recommend it)
Cytoscape 2.8 Tips & Tricks
• Memory
– Cytoscape uses lots of it
– Doesn’t like to let go of it
– An occasional restart when working with large networks is a
good thing
– Destroy views when you don’t need them
– Java doesn’t give us a good way to get the memory right at start
time
• Since version 2.7, Cytoscape does a much better job at “guessing” good
default memory sizes than previous versions
Cytoscape 2.8 Tips & Tricks
• .cytoscape directory
– Your defaults and any plugins downloaded from the plugin
manager will go here
– Sometimes, if things get really messed up, deleting (or
renaming) this directory can give you a “clean slate”
• Plugin manager
– “Outdated” doesn’t necessarily mean “won’t work”
– Plugin authors don’t always update their plugins
immediately after new releases
Cytoscape 3.0